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Xing Cui

7 accepted papers

2026

T2Agent: A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search

AAAI 2026technical

Real-world multimodal misinformation often arises from mixed forgery sources, requiring dynamic reasoning and adaptive verification. However, existing methods mainly rely on static pipelines and limited tool usage, limiting their ability to handle such complexity and diversity. To address this chall

Cited by 0SourcePDFScholar
2026

VFCionX: Bridging Large and Small Models for Robust Vulnerability-Fixing Commit Identification

AAAI 2026technical

Vulnerability-Fixing Commit Identification(VFCI) is a critical task in software security maintenance that aims to automatically identify code commits that patch security vulnerabilities. However, existing approaches face challenges in handling low-quality commit messages and entangled commits, which

Cited by 0SourcePDFScholar
2025

MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs

ICLR 2025poster

Current multimodal misinformation detection (MMD) methods often assume a single source and type of forgery for each sample, which is insufficient for real-world scenarios where multiple forgery sources coexist. The lack of a benchmark for mixed-source misinformation has hindered progress in this fie…

Cited by 0SourcePDFScholar
2025

Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs

NeurIPS 2025poster

The increasing deployment of Large Vision-Language Models (LVLMs) raises safety concerns under potential malicious inputs. However, existing multimodal safety evaluations primarily focus on model vulnerabilities exposed by static image inputs, ignoring the temporal dynamics of video that may induce…

Cited by 0SourcecodeScholar
2024

InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser

ECCV 2024poster

"Stylized text-to-image generation focuses on creating images from textual descriptions while adhering to a style specified by reference images. However, subtle style variations within different reference images can hinder the model from accurately learning the target style. In this paper, we propos…

2024

Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner

NeurIPS 2024poster

Flexible and accurate drag-based editing is a challenging task that has recently garnered significant attention. Current methods typically model this problem as automatically learning "how to drag" through point dragging and often produce one deterministic estimation, which presents two key limitati…

2023

ChatEdit: Towards Multi-turn Interactive Facial Image Editing via Dialogue

EMNLP 2023long main

This paper explores interactive facial image editing through dialogue and presents the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this context. ChatEdit is constructed from the CelebA-HQ dataset, incorporating annotated multi-turn dialogues corresponding to…

Cited by 0SourceScholar